{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "1c911de6-4a81-40e9-bd4b-ff6ab86dd686",
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'numpy'",
     "output_type": "error",
     "traceback": [
      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
      "\u001b[31mModuleNotFoundError\u001b[39m                       Traceback (most recent call last)",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[14]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m      1\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mzai\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m ZhipuAiClient\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnumpy\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnp\u001b[39;00m\n",
      "\u001b[31mModuleNotFoundError\u001b[39m: No module named 'numpy'"
     ]
    }
   ],
   "source": [
    "from zai import ZhipuAiClient\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c88be609-3146-4502-a726-1fc98afc6639",
   "metadata": {},
   "outputs": [],
   "source": [
    "client = ZhipuAiClient(\n",
    "    base_url=\"https://api.siliconflow.cn/v1\",\n",
    "    api_key=\"sk-knraanmfzbmiaqemqzsfxusqzvrcxuuioomrdknougvokjkl\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "99c1e9a3-abb2-4495-b5b2-b85bd138b36e",
   "metadata": {},
   "outputs": [],
   "source": [
    "documents = [\n",
    "    \"美食非常美味，服务员也很友好。\",\n",
    "    \"这部电影既刺激又令人兴奋。\",\n",
    "    \"阅读书籍是扩展知识的好方法。\"\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a03379d9-ed81-48a0-9c81-079b8299c760",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "response = client.embeddings.create(\n",
    "    model=\"BAAI/bge-large-zh-v1.5\",\n",
    "    input=documents\n",
    ")\n",
    "\n",
    "for data in response.data:\n",
    "    print(data.embedding)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ddaeab58-c067-4045-99df-439ff7c54dbf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 余弦相似度计算"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "llm_learn",
   "language": "python",
   "name": "llm_learn"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
